Dual or multi-energy spectral computed tomography (CT) systems can reveal the densities of different materials in an object and generate images acquired at multiple monochromatic x-ray energy levels. In the absence of object scatter, a system derives the behavior at a different energy based on a signal from two regions of photon energy in the spectrum: the low-energy and the high-energy portions of the incident x-ray spectrum. In a given energy region of medical CT, two physical processes dominate the x-ray attenuation: Compton scattering and the photoelectric effect. The detected signals from two energy regions provide sufficient information to resolve the energy dependence of the material being imaged. Detected signals from the two energy regions provide sufficient information to determine the relative composition of an object composed of two hypothetical materials.
Different approaches have been developed to realize dual energy or spectral imaging. To name a few, dual x-ray source and detector, single x-ray source and detector with multiple acquisitions at different peak kilovoltage (kVp) or interleaved with fast kVp switching capability, and single x-ray source with an energy discriminative detector are leading techniques. In a single x-ray source and detector arrangement, a conventional third generation CT system may acquire projections sequentially at different kVp levels, which changes the peak and spectrum of energy of the incident photons comprising the emitted x-ray beams. Two scans are acquired—either back-to-back sequentially in time where the scans require two rotations around the subject, hereinafter referred to as rotate-rotate dual energy, or interleaved as a function of the rotation angle requiring one rotation around the subject, hereinafter referred to as fast-switching dual energy, in which the x-ray tube operates, for instance, at 80 kVp and 140 kVp potentials.
Once dual or multi-energy data is obtained, a basis material decomposition (BMD) algorithm may be applied in order to image two distinct materials, such as water and iodine, as examples. A conventional BMD algorithm is based on the concept that, in an energy region for medical CT, the x-ray attenuation of any given material can be represented by a proper density mix of two materials with distinct x-ray attenuation properties, referred to as the basis materials. The BMD algorithm computes two material density images that represent the equivalent density of one of the basis materials based on the measured projections at high and low x-ray photon energy spectra, respectively. The material density images may be further converted to form monochromatic images at other desired monochromatic energies.
Typically the measured projections at high and low x-ray photon energy spectra are equally treated when generating material density images. However, the x-ray attenuation properties of the basis materials may affect the material density differently at different energy levels. Furthermore, fast-switching dual energy CT systems may interpolate high and low energy projection data to obtain complete projection datasets, potentially introducing noise to the data. As a result, material density images and subsequently formed monochromatic images may feature a degraded image quality due to an unnecessary dependence on interpolated data.